Examining the Implications of Deepfakes for Election Integrity

TL;DR

Deepfake technology poses significant threats to election integrity by enabling disinformation campaigns, requiring improved detection methods and policy responses to mitigate manipulation and misinformation in political contexts.

Contribution

This paper analyzes deepfake generation methods, evaluates existing detection techniques, and provides policy recommendations to address deepfake-related threats in elections.

Findings

Existing detection methods have notable limitations.

Deepfakes can both reinforce narratives and manipulate perceptions.

Policy gaps need to be addressed to mitigate risks.

Abstract

It is becoming cheaper to launch disinformation operations at scale using AI-generated content, in particular 'deepfake' technology. We have observed instances of deepfakes in political campaigns, where generated content is employed to both bolster the credibility of certain narratives (reinforcing outcomes) and manipulate public perception to the detriment of targeted candidates or causes (adversarial outcomes). We discuss the threats from deepfakes in politics, highlight model specifications underlying different types of deepfake generation methods, and contribute an accessible evaluation of the efficacy of existing detection methods. We provide this as a summary for lawmakers and civil society actors to understand how the technology may be applied in light of existing policies regulating its use. We highlight the limitations of existing detection mechanisms and discuss the areas where policies and regulations are required to address the challenges of deepfakes.